Scaling Transition Intelligence

The document demonstrates how banks can move beyond high-level corporate ambition assessments by using bottom-up, asset-level data to project emissions trajectories. Using ArcelorMittal as a case study, it shows that comparing these projections against company targets and global/regional transition pathways reveals 'execution gaps' and exposure to transition risks. This 'transition intelligence' allows sustainability, risk, and front-office teams to identify specific technology lock-in risks and structure tailored transition-finance products.

• Traditional transition assessments by financial institutions often focus on past capital expenditures and high-level governance, which fails to reveal how specific assets or technologies are exposed to future risks. Forward-looking asset-level data allows for a more granular analysis that is useful for front-office and credit risk teams, not just sustainability teams.
• A case study of ArcelorMittal indicates that the company is projected to fall short of its 2030 emissions intensity targets based on current public investment plans. This 'execution gap' creates opportunities for financial institutions to engage with clients to identify barriers and structure transition-finance products to help meet those targets.
• Comparing corporate investment pipelines to global transition pathways, such as those from the IEA, helps financial institutions assess transition risk. ArcelorMittal's projected trajectory is misaligned with the IEA Net Zero Emissions by 2050 (NZE), Announced Pledges Scenario (APS), and Stated Policy Scenario (STEPS), suggesting exposure to risks if policy or markets tighten suddenly.
• Regional transition pathways provide more granular intelligence than global ones. Analysis using Mission Possible Partnership (MPP) Europe-specific scenarios showed ArcelorMittal is misaligned with 'Carbon cost' and 'Technology moratorium' pathways, highlighting the importance of linking assets to local risk drivers.
• Asset-level analysis reveals that while ArcelorMittal is increasing its use of lower-carbon direct reduced iron–electric arc furnace (DRI-EAF) technology, it also plans to expand carbon-intensive blast furnace–basic oxygen furnace (BF-BOF) capacity. Because BF-BOF assets have a long economic life of approximately 20 years, this creates a risk of carbon lock-in.
• Transition intelligence derived from asset-level data serves three primary functions within a bank: sustainability teams can assess portfolio-level climate targets; risk teams can develop sectoral risk appetites and ex ante risk assessments; and front-office teams can identify specific project finance opportunities for low-carbon technology build-out.

APA

RMI (2026). Scaling Transition Intelligence. https://rmi.org/resources/scaling-transition-intelligence/

Chicago

RMI. Scaling Transition Intelligence. 2026. https://rmi.org/resources/scaling-transition-intelligence/.

Wikipedia

{{cite report |author=RMI |title=Scaling Transition Intelligence |date=13 April 2026 |url=https://rmi.org/resources/scaling-transition-intelligence/ |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{rmi2026scaling, author = {{RMI}}, title = {{Scaling Transition Intelligence}}, institution = {RMI}, year = {2026}, month = apr, url = {https://rmi.org/resources/scaling-transition-intelligence/}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }